Data Science’s Influence on Commercial Real Estate

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All science is based on statistics. Science relies on data, whether it is used to prove a hypothesis or to create a mathematical prediction. Statistics even became its own subset of mathematics. Once computers became the primary tool for scientists to collect and analyze large amounts of data, a new subset of computer science was proposed. The idea behind “data science” was to create new and better ways to prepare, present, and model data and push the boundaries of statistics beyond theory and practice.

Now data science is a household word (even though most people probably couldn’t define its meaning) and has bled into every facet of our lives. Businesses in every industry already harness the predictive power of statistics thanks to data science tools and techniques. But one industry in which data science has not materially changed is real estate. 

There are good reasons for this. Real estate data comes from various sources, so it is not standardized enough to be useful. For a real estate company to be able to run models on properties, all of the company’s data has to be documented in the exact same way. Even something as simple as a non-disclosed unit number could throw off a statistical model. For small queries, data can always be double-checked by a human, but the point of data science is to enable statistics at scale

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